CN109067670B - CDN scheduling method and CDN scheduling equipment - Google Patents
CDN scheduling method and CDN scheduling equipment Download PDFInfo
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Abstract
The application relates to a CDN scheduling method, which comprises the following steps: acquiring a scheduling strategy of a current period, wherein the scheduling strategy is determined based on a genetic algorithm; receiving a content access request sent by a client, wherein the content access request comprises a DNS message for IP query through a Local DNS; determining a CDN device set which should be served in a region corresponding to the IP of the Local DNS; selecting at least one CDN device in the CDN device set according to the scheduling strategy; and distributing the request to the selected CDN device for processing.
Description
Technical Field
The present application relates to the field of CND device scheduling, and in particular, to a CDN scheduling method and a CDN scheduling device.
Background
The Content Delivery Network (CDN) has a basic idea of avoiding bottlenecks and links on the internet that may affect data transmission speed and stability as much as possible, so that Content transmission is faster and more stable. The policy of CDN bandwidth scheduling based on the DNS is a very complicated problem, due to the limitation of the DNS, arbitrary scheduling of traffic cannot be performed, and only traffic in a certain area can be evenly distributed to node CDN devices, which causes very complicated bandwidth scheduling policy calculation.
Disclosure of Invention
In order to overcome the problems in the related art at least to a certain extent, the present application provides a CDN scheduling method and a CDN scheduling device.
The scheme of the application is as follows:
according to a first aspect of an embodiment of the present application, a CDN scheduling method is provided, including:
acquiring a scheduling strategy of a current period, wherein the scheduling strategy is determined based on a genetic algorithm;
receiving a content access request sent by a client, wherein the content access request comprises a DNS message for IP query through a Local DNS;
determining a CDN device set which should be served in a region corresponding to the IP of the Local DNS;
selecting at least one CDN device in the CDN device set according to the scheduling strategy;
and distributing the request to the selected CDN device for processing.
Preferably, in combination with the above, in one possible implementation manner of the present application, the method further includes:
calculating a scheduling strategy of the current period in the previous period of the current period;
wherein the calculating the scheduling policy of the current cycle comprises:
randomly initializing population genes, wherein each gene corresponds to a scheduling strategy;
predicting the bandwidth of the whole network in the current period, and setting a gene evolution direction according to the bandwidth of the whole network;
evolving initial population genes towards the gene evolution direction based on a genetic algorithm to obtain optimal genes;
and determining the scheduling strategy corresponding to the optimal gene as the scheduling strategy of the current period.
Preferably, in combination with the above, in one possible implementation manner of the present application, the evolving an initial population of genes towards the gene evolution direction based on a genetic algorithm to obtain an optimal gene includes:
calculating the sum of scores of all evaluation values of the scheduling strategy corresponding to each gene from the initial population gene;
if the required evaluation value score is achieved, whether the set constraint condition is met or not is evaluated;
if the evaluation value score does not meet the requirement, discarding the evaluation value score;
if the set constraint conditions are met, sequencing according to the high and low values of the scores of the gene evaluation values, directly putting the gene with the highest score of the evaluation values into a child population, and selecting, inheriting and mutating all parent genes to generate the child population;
calculating the sum of scores of all evaluation values of the scheduling strategy corresponding to each gene of the offspring gene population;
repeating the steps until a preset iteration number is reached or a preset gene evolution success condition is met;
and outputting the optimal gene corresponding to the scheduling strategy with the highest evaluation value.
Preferably, in combination with the above, in one possible implementation manner of the present application, the evaluation value includes: CDN device bandwidth cost, CDN device quality of service, and whether the gene evolution direction is satisfied.
Preferably, with reference to the above contents, in a possible implementation manner of the present application, the constraint condition is that the CDN device coverage area is a serviceable area of the CDN device, the CDN device service bandwidth is smaller than the maximum service bandwidth of the CDN device, and all domain names have CDN device services in all areas.
Preferably, in combination with the above, in a possible implementation manner of the present application, the setting a gene evolution direction according to the bandwidth of the whole network includes:
when the bandwidth of the whole network is larger than the sum of the expected charging bandwidths of the CDN equipment, setting the CDN equipment using free bandwidth at the current moment as a gene evolution direction;
when the bandwidth of the whole network is not less than the sum of the expected cost bandwidths of the CDN equipment and not more than the sum of the expected charging bandwidths of the CDN equipment, the cost of the CDN equipment is prioritized, and the service quality is set as an auxiliary direction of gene evolution;
and when the bandwidth of the whole network is smaller than the sum of the expected cost bandwidths of the CDN equipment, preferentially setting the service quality of the CDN equipment as a gene evolution direction.
Preferably, in combination with the above, in one possible implementation manner of the present application, the determining whether the gene evolution direction is satisfied includes:
if the CDN equipment using free bandwidth at the current moment is set as the gene evolution direction, calculating the sum of the bandwidth costs of all the CDN equipment providing service in the scheduling strategy, and determining the scheduling strategy which meets the requirement that the cost of the CDN equipment using the free bandwidth is zero and does not additionally increase the sum of the costs of other CDN equipment as the requirement of the gene evolution direction;
if the cost of the CDN equipment is prioritized and the service quality is set as an auxiliary service direction, calculating the sum of the bandwidth costs of all the CDN equipment providing the service in the scheduling strategy and obtaining the service quality evaluation value of all the CDN equipment providing the service, wherein the sum of the bandwidth costs of all the CDN equipment is lower, and the scheduling strategy with the higher service quality evaluation value meets the gene evolution direction;
if the service quality of the CDN equipment is preferentially set to be the gene evolution direction, calculating the sum of the bandwidth cost of all CDN equipment providing services in the scheduling strategy and obtaining the service quality evaluation value of all CDN equipment providing services, wherein the scheduling strategy meets the requirement that the service quality evaluation value of all CDN equipment is high and the sum of the cost of other CDN equipment is not additionally increased so as to meet the gene evolution direction.
Preferably, in combination with the above, in a possible implementation manner of the present application, the predicting the full network bandwidth of the current period includes:
determining a long-term prediction period where the current period is located and a corresponding long-term prediction value; and the number of the first and second groups,
predicting a short-term predicted value of the current period;
and correcting the long-term predicted value by adopting the short-term predicted value, and predicting to obtain the whole network bandwidth of the current period.
Preferably, in a possible implementation form of the application, in combination with the above, characterized in that,
the current period and the last period take one hour as a period.
According to a second aspect of the embodiments of the present application, there is provided a CDN scheduling device, including:
the scheduling module is used for acquiring a scheduling strategy of the current period, and the scheduling strategy is determined based on a genetic algorithm;
the receiving module is used for receiving a content access request sent by a client, wherein the content access request comprises a DNS message for IP query through a Local DNS;
the searching module is used for determining a CDN device set which is to be served in a region corresponding to the IP of the Local DNS;
the scheduling module is further configured to select at least one CDN device in the CDN device set according to the scheduling policy;
and the execution module is used for distributing the request to the selected CDN device for processing.
The technical scheme provided by the application can comprise the following beneficial effects:
in the method, the scheduling strategies of the CDN devices in the current period are calculated through a genetic algorithm, an optimal scheduling strategy is obtained from a plurality of CDN device scheduling strategies, at least one CDN device is selected from a CDN device set according to the optimal scheduling strategy, a task request is sent to the CDN devices to be processed, the utilization rate of bandwidth of the CDN devices is improved, and the experience degree of a user is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flowchart of a CDN scheduling method according to an embodiment of the present application;
fig. 2 is a flowchart of a CDN scheduling method according to another embodiment of the present application;
FIG. 3 is a flow chart of a genetic algorithm provided by yet another embodiment of the present application;
fig. 4 is a structural diagram of a CDN scheduling device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of a CDN scheduling method and CDN scheduling apparatus consistent with certain aspects of the present application, as detailed in the appended claims.
Fig. 1 is a flowchart of a CDN scheduling method according to an embodiment of the present application, and with reference to fig. 1, the method includes:
s101: acquiring a scheduling strategy of a current period, wherein the scheduling strategy is determined based on a genetic algorithm;
the genetic algorithm is a calculation model for simulating the biological evolution process of natural selection and genetic mechanism of Darwinian biological evolution theory, is a method for searching an optimal solution by simulating the natural evolution process, and can obtain an optimal scheduling strategy calculated from a plurality of scheduling strategies in the current period through the genetic algorithm.
S102: receiving a content access request sent by a client, wherein the content access request comprises a DNS message for IP query through a Local DNS (Local domain name);
the method comprises the steps that a client side obtains an IP address through a Local DNS, and receives an IP query request of the Local DNS, wherein the IP query of the Local DNS is initiated to the Local DNS by the client side;
and returning the IP address corresponding to the Local DNS, and then returning the IP address to the client by the Local DNS.
And receiving a content access request which is sent by the client and contains the IP address through the Local DNS.
S103: determining a CDN device set which should be served in a region corresponding to the IP of the Local DNS;
in the whole country, the regions can be divided according to provinces, more detailed points can be divided according to cities, and CDN devices which can be served by each region are a CDN device set; different zones correspond to different IP addresses of the Local DNS.
And determining the CDN device set which the corresponding region should serve by determining the IP address corresponding to the Local DNS.
S104: selecting at least one CDN device in the CDN device set according to the scheduling strategy;
s105: and distributing the request to the selected CDN equipment for processing.
The request is distributed to the selected CDN device for processing, that is, scheduling execution is performed, where the scheduling execution System is implemented by a DNS (Domain Name System) System and a GHR System, and the bandwidth is guided by a DNS (HyperText Transfer Protocol) 302 mode and an HTTP DNS mode, respectively, so as to achieve an effect required by a scheduling policy.
Before the scheduling policy is calculated, various parameter index information of the CDN device needs to be prepared. The method comprises the following steps:
and automatically acquiring the static parameters and the dynamic parameters of the CDN equipment.
The obtaining of the static parameters of the CDN device includes: acquiring a set of serviceable areas of each CDN device, the maximum borne bandwidth of the CDN device, the guaranteed bandwidth of the CDN device, the bandwidth cost of the CDN device and the charging mode of the CDN device. And if the CDN equipment parameters change in the operation process, the CDN equipment information is automatically updated.
The obtaining of the dynamic parameters of the CDN device includes: obtaining relevant indexes generated by the CDN equipment in operation, including: whether CDN equipment networks are communicated or not; utilization rates of CDN device memory, CPU, I/O, network and the like; the method for automatically obtaining the performance indexes of all the domains served on different CDN devices comprises the following steps: success rate, delay, slow speed ratio, etc.
Automatically acquiring domain name bandwidth information: and counting the bandwidth information of all the domain names in real time, classifying the domain names according to regions, and counting the bandwidth data of all the domain names in different regions every 5 minutes.
The preferable scheduling strategy is a scheduling strategy with low cost and good CDN device service quality.
In the method, the scheduling strategies of the CDN devices in the current period are calculated through a genetic algorithm, an optimal scheduling strategy is obtained from a plurality of CDN device scheduling strategies, at least one CDN device is selected from a CDN device set according to the optimal scheduling strategy, a task request is sent to the CDN devices to be processed, the utilization rate of bandwidth of the CDN devices is improved, and the experience degree of a user is improved.
The scheduling policy of the current cycle is obtained in the previous cycle of the current cycle. Generally, the scheduling policy of the current period is predicted one hour before the current period. Fig. 2 is a flowchart of a CDN scheduling method according to another embodiment of the present application, with reference to fig. 2,
calculating a scheduling strategy of the current period in the previous period of the current period;
wherein, calculating the scheduling policy of the current period comprises:
s201, randomly initializing population genes, wherein each gene corresponds to a scheduling strategy;
a scheduling strategy is abstracted into a binary coded gene individual by the following method: all the regions are arranged according to a fixed sequence, such as: p1, P2, P3, traverse each region, and arrange the CDN capable of service devices of each region, such as: p1(n1, n2), P2(n3, n4), P3(n1, n3, n5), CDN-capable devices representing P1 region are n1, n2, and so on. At the same time, all domain names are arranged, such as: d1(P1(n1, n2), P2(n3, n4), P3(n1, n3, n5)), D2(P1(n1, n2), P2(n3, n4), P3(n1, n3, n 5)). If a CDN device in a certain region of a certain domain name provides service, it corresponds to position 1 in the arrangement, otherwise it corresponds to position 0, so that a string of combinations of 0 and 1 is obtained, that is, a binary-coded gene, such as: the strategy for gene 01010111001101 is: domain name D1: the region P1 serves CDN devices as: n2, region P2 serving CDN devices is: n4, region P3 serving CDN devices is: n3, n 5; domain name D2: the region P1 serves CDN devices as: n1, region P2 serving CDN devices is: n4, region P3 serving CDN devices is: n1, n 5.
In some embodiments, the initial gene population number is set to 800 and the maximum number of iterations is set to 50. That is, 800 scheduling strategies are screened, and the screening process is repeated for 50 times.
S202, predicting the bandwidth of the whole network in the current period, and setting the gene evolution direction according to the bandwidth of the whole network;
predicting the full network bandwidth of the current period, comprising:
determining a long-term prediction period of the current period and a corresponding long-term prediction value; and the number of the first and second groups,
predicting a short-term predicted value of the current period;
and correcting the long-term predicted value by adopting the short-term predicted value, and predicting to obtain the whole network bandwidth of the current period.
And (3) long-term prediction: according to the historical data of the bandwidth of the domain names in the regions, after comprehensive analysis, the bandwidths of all the domain names in all the regions are predicted, the prediction is mainly carried out by taking a week as a unit, meanwhile, the influence caused by holidays is considered, the holidays are divided by taking the time length as a classification standard, the long-term prediction period is one month, and the trend of the bandwidth for one month is predicted in the two prediction modes, namely the long-term prediction value. In order to ensure the accuracy of prediction, the bandwidth history data is the bandwidth history data of more than 1 year.
Short-term prediction: and acquiring real-time data of the domain name in the regional bandwidth, and obtaining a short-term predicted value, generally from one hour to one day, by combining a monthly bandwidth prediction curve obtained by long-term prediction. And meanwhile, correcting the long-term predicted value according to the short-term predicted value.
The method for setting the gene evolution direction according to the bandwidth of the whole network comprises the following steps:
when the bandwidth of the whole network is larger than the sum of the expected charging bandwidths of the CDN equipment, setting the CDN equipment using free bandwidth at the current moment as a gene evolution direction;
when the bandwidth of the whole network is not less than the sum of the expected cost bandwidths of the CDN equipment and not more than the sum of the expected charging bandwidths of the CDN equipment, the cost of the CDN equipment is prioritized, and the service quality is set as an auxiliary direction of gene evolution;
and when the bandwidth of the whole network is smaller than the sum of the expected cost bandwidths of the CDN equipment, preferentially setting the service quality of the CDN equipment as a gene evolution direction.
The whole network bandwidth refers to the whole network bandwidth of a certain operator, including all domain names of the operator.
Expected cost bandwidth for CDN devices: acquiring a lowest bandwidth allocation value of the CDN device as an expected cost bandwidth of the CDN device; the actual charging bandwidth of the CDN device can rise along with the time, and if the actual charging bandwidth of the CDN device exceeds the expected cost bandwidth of the CDN device, the expected cost bandwidth of the CDN device is replaced by the actual charging bandwidth of the CDN device.
Expected charging bandwidth of CDN device: after the total network bandwidth is predicted, sequentially distributing CDN devices from the maximum bandwidth of one month, processing the task request by using the free bandwidth of the CDN devices, and finally if the free bandwidth of all the CDN devices is completely used and the total network bandwidth is still remained, determining the remained total network bandwidth as the total network expected charging bandwidth.
Free bandwidth for CDN devices: the method is characterized in that the attribute characteristics of CDN equipment and the regional bandwidth change characteristics are integrated, the characteristic that the charging is not carried out on 5% of bandwidth before a 95 charging node is utilized, a use plan of free bandwidth time points of each CDN equipment in one month is made according to long-term prediction, a time period for the occurrence of the free bandwidth of each CDN equipment is planned, and a certain margin is reserved for the free bandwidth of each CDN equipment to deal with the emergency. For example, if the free bandwidth time point of each CDN device lasts 24 hours, the first 23.5 hours of the free bandwidth of the CDN device is preferentially used, and the remaining 0.5 hour of the free bandwidth is used to cope with an emergency.
S203, evolving the initial population genes towards the gene evolution direction based on the genetic algorithm to obtain the optimal genes; the method comprises the following steps:
calculating the sum of scores of all evaluation values of the scheduling strategy corresponding to each gene from the initial population gene;
if the required evaluation value score is achieved, whether the set constraint condition is met or not is evaluated;
if the evaluation value score does not meet the requirement, discarding the evaluation value score;
if the set constraint conditions are met, sequencing according to the high and low values of the scores of the gene evaluation values, directly putting the gene with the highest score of the evaluation values into a child population, and selecting, inheriting and mutating all parent genes to generate the child population;
calculating the sum of scores of all evaluation values of a scheduling strategy corresponding to each gene of the filial generation gene population;
repeating the steps until a preset iteration number is reached or a preset gene evolution success condition is met;
and outputting the optimal gene corresponding to the scheduling strategy with the highest evaluation value.
The condition for successful preset gene evolution is that the total network bandwidth cost generated by scheduling according to the scheduling strategy corresponding to the gene reaches the preset total network bandwidth cost.
The evaluation values include: CDN device bandwidth cost, CDN device quality of service, and whether the gene evolution direction is satisfied.
The bandwidth cost of the CDN equipment and the service quality of the CDN equipment can be directly obtained.
Judging whether the gene evolution direction is met or not, comprising the following steps:
if the CDN equipment using free bandwidth at the current moment is set as the gene evolution direction, calculating the sum of the bandwidth costs of all the CDN equipment providing service in the scheduling strategy, and determining the scheduling strategy which meets the requirement that the cost of the CDN equipment using the free bandwidth is zero and does not additionally increase the sum of the costs of other CDN equipment as the requirement of the gene evolution direction;
after the free bandwidth of the CDN device is used, if the bandwidth of the entire network still remains, the sum of the costs of not additionally increasing other CDN devices is also considered when the bandwidth of other charged CDN devices is used.
If the cost of the CDN equipment is prioritized and the service quality is set as an auxiliary direction of gene evolution, calculating the sum of the bandwidth costs of all CDN equipment providing services in the scheduling strategy and obtaining the service quality evaluation values of all CDN equipment providing services, wherein the sum of the bandwidth costs of all CDN equipment is lower, and the scheduling strategy with the higher service quality evaluation value meets the direction of gene evolution;
if the service quality of the CDN equipment is preferentially set to be the gene evolution direction, calculating the sum of the bandwidth cost of all CDN equipment providing services in the scheduling strategy and obtaining the service quality evaluation value of all CDN equipment providing services, wherein the scheduling strategy meets the requirement that the service quality evaluation value of all CDN equipment is high and the sum of the cost of other CDN equipment is not additionally increased so as to meet the gene evolution direction.
And allocating weight values to the bandwidth cost of the CDN equipment, the service quality of the CDN equipment and whether the CDN equipment meets the gene evolution direction, scoring each evaluation value in a percentage system, and then obtaining the total score of the evaluation values of the scheduling strategy according to the allocated weight values.
The constraint conditions are that the CDN device coverage area is a serviceable area, the CDN device service bandwidth is smaller than the maximum service bandwidth, and all domain names are served by CDN devices in all areas.
The preset number of iterations may be 50.
Wherein, if the set constraint condition is satisfied, the genes are sorted according to the score of the gene evaluation value, the gene with the highest score of the evaluation value is directly put into the offspring population, all the parent genes are selected, inherited and mutated to generate the offspring population, specifically,
selecting: selecting genes in the population by a roulette wheel selection method with high probability of selecting the genes with high evaluation value scores;
heredity: selecting two parent gene individuals, randomly exchanging the gene segments of the parents, for example, 01010111001101 and 11010111000101 represent the genes of the two scheduling strategies respectively, and after the exchange, 01010111000101 and 11010111001101 can be obtained;
mutation: the scheduling strategy of extracting the offspring genetic individuals, namely achieving the required evaluation value score, replacing some genes, changing 0 to 1, and changing 1 to 0, such as changing 1001101 genes to 0110010,1000001, etc., is changed accordingly.
The parent gene with the highest evaluation value score is not only directly put into a child population, but also serves as a parent sample for selection, heredity and mutation.
In some embodiments, if the evaluation value score does not meet the requirement, the scheduling policy that does not meet the requirement evaluation value score can be selected to perform substantial deduction, and the scheduling policy continues to participate in the processes of selection, inheritance and mutation. Since some genes whose evaluation values do not meet the requirements may not meet the requirements due to the first half of genes, but the second half of genes are excellent, it is possible to inherit the latter half to offspring by gene exchange, thereby maintaining the diversity of genes.
And S204, determining the scheduling strategy corresponding to the optimal gene as the scheduling strategy of the current period.
And determining a scheduling strategy corresponding to the optimal gene calculated by the genetic algorithm as a scheduling strategy of the current period, scheduling according to the scheduling strategy of the current period, selecting at least one CDN device in the CDN device set, and sending a task request to the selected CDN device for processing.
According to a second aspect of the present application, there is provided a CDN scheduling device, including:
a scheduling module 43, configured to obtain a scheduling policy of a current period, where the scheduling policy is determined based on a genetic algorithm;
a receiving module 41, configured to receive a content access request sent by a client, where the content access request includes a DNS packet for performing IP query through Local DNS;
a searching module 42, configured to determine a CDN device set that should be served in a region corresponding to the IP of the Local DNS;
the scheduling module 43 is further configured to select at least one CDN device in the CDN device set according to a scheduling policy;
and an execution module 44, configured to allocate the request to the selected CDN device for processing.
The CDN scheduling device in some embodiments further includes a data acquisition module, configured to automatically acquire the static parameter and the dynamic parameter of the CDN device.
The obtaining of the static parameters of the CDN device includes: acquiring a set of serviceable areas of each CDN device, the maximum borne bandwidth of the CDN device, the guaranteed bandwidth of the CDN device, the cost bandwidth of the CDN device and the charging mode of the CDN device. And if the CDN equipment parameters change in the operation process, the CDN equipment information is automatically updated.
The obtaining of the dynamic parameters of the CDN device includes: obtaining relevant indexes generated by the CDN equipment in operation, including: whether CDN equipment networks are communicated or not; utilization rates of CDN device memory, CPU, I/O, network and the like; the method for automatically obtaining the performance indexes of all the domains served on different CDN devices comprises the following steps: success rate, delay, slow speed ratio, etc.
Automatically acquiring domain name bandwidth information: and counting the bandwidth information of all the domain names in real time, classifying the domain names according to regions, and counting the bandwidth data of all the domain names in different regions every 5 minutes.
And the data storage module is used for storing the data acquired by the data acquisition module.
And the long-term prediction module is used for performing long-term prediction.
And the short-term prediction module is used for performing short-term prediction.
And the service quality module is used for acquiring the service quality evaluation value of each CDN device.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present application, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (8)
1. A CDN scheduling method is characterized by comprising the following steps:
acquiring a scheduling strategy of a current period, wherein the scheduling strategy is determined based on a genetic algorithm;
receiving a content access request sent by a client, wherein the content access request comprises a DNS message for IP query through a Local DNS;
determining a CDN device set which should be served in a region corresponding to the IP of the Local DNS;
selecting at least one CDN device in the CDN device set according to the scheduling strategy;
distributing the request to the selected CDN equipment for processing;
the scheduling strategy of the current period is calculated in the previous period of the current period;
calculating the scheduling policy of the current cycle comprises:
randomly initializing population genes, wherein each gene corresponds to a scheduling strategy;
predicting the bandwidth of the whole network in the current period, and setting a gene evolution direction according to the bandwidth of the whole network;
evolving initial population genes towards the gene evolution direction based on a genetic algorithm to obtain optimal genes;
determining a scheduling strategy corresponding to the optimal gene as a scheduling strategy of the current period;
wherein, the setting of the gene evolution direction according to the whole network bandwidth comprises:
when the bandwidth of the whole network is larger than the sum of the expected charging bandwidths of the CDN equipment, setting the CDN equipment using free bandwidth at the current moment as a gene evolution direction;
when the bandwidth of the whole network is not less than the sum of the expected cost bandwidths of the CDN equipment and not more than the sum of the expected charging bandwidths of the CDN equipment, the cost of the CDN equipment is prioritized, and the service quality is set as an auxiliary direction of gene evolution;
and when the bandwidth of the whole network is smaller than the sum of the expected cost bandwidths of the CDN equipment, preferentially setting the service quality of the CDN equipment as a gene evolution direction.
2. The method of claim 1, wherein the evolving an initial population of genes toward the gene evolution based on a genetic algorithm to obtain optimal genes comprises:
calculating the sum of scores of all evaluation values of the scheduling strategy corresponding to each gene from the initial population gene;
if the required evaluation value score is achieved, whether the set constraint condition is met or not is evaluated;
if the evaluation value score does not meet the requirement, discarding the evaluation value score;
if the set constraint conditions are met, sequencing according to the high and low values of the scores of the gene evaluation values, directly putting the gene with the highest score of the evaluation values into a child population, and selecting, inheriting and mutating all parent genes to generate the child population;
calculating the sum of scores of all evaluation values of the scheduling strategy corresponding to each gene of the offspring gene population;
repeating the steps until a preset iteration number is reached or a preset gene evolution success condition is met;
and outputting the optimal gene corresponding to the scheduling strategy with the highest evaluation value.
3. The method of claim 2, wherein the evaluating comprises: CDN device bandwidth cost, CDN device quality of service, and whether the gene evolution direction is satisfied.
4. The method of claim 2, wherein the constraints are that the CDN device coverage area is its serviceable area, the CDN device service bandwidth is less than its maximum service bandwidth, and all domain names are served by CDN devices in all areas.
5. The method of claim 3, wherein determining whether the gene evolution direction is satisfied comprises:
if the CDN equipment using free bandwidth at the current moment is set as the gene evolution direction, calculating the sum of the bandwidth costs of all the CDN equipment providing service in the scheduling strategy, and determining the scheduling strategy which meets the requirement that the cost of the CDN equipment using the free bandwidth is zero and does not additionally increase the sum of the costs of other CDN equipment as the requirement of the gene evolution direction;
if the cost of the CDN equipment is prioritized and the service quality is set as an auxiliary direction of gene evolution, calculating the sum of the bandwidth costs of all CDN equipment providing services in the scheduling strategy and obtaining the service quality evaluation values of all CDN equipment providing services, wherein the sum of the bandwidth costs of all CDN equipment is lower, and the scheduling strategy with the higher service quality evaluation value meets the direction of gene evolution;
if the service quality of the CDN equipment is preferentially set to be the gene evolution direction, calculating the sum of the bandwidth cost of all the CDN equipment providing the service in the scheduling strategy and obtaining the service quality evaluation value of all the CDN equipment providing the service, wherein the scheduling strategy meets the requirement that the service quality evaluation value of all the CDN equipment is high and the sum of the cost of other CDN equipment is not additionally increased and meets the gene evolution direction.
6. The method of claim 1, wherein predicting the full network bandwidth of the current period comprises:
determining a long-term prediction period where the current period is located and a corresponding long-term prediction value; and (c) a second step of,
predicting a short-term predicted value of the current period;
and correcting the long-term predicted value by adopting the short-term predicted value, and predicting to obtain the whole network bandwidth of the current period.
7. The method of claim 6,
the current period and the last period take one hour as a period.
8. A CDN scheduling device, comprising:
the scheduling module is used for acquiring a scheduling strategy of the current period, and the scheduling strategy is determined based on a genetic algorithm;
the receiving module is used for receiving a content access request sent by a client, wherein the content access request comprises an IP address obtained through a Local DNS;
the searching module is used for determining a CDN device set which is to be served in a region corresponding to the Local DNS;
the scheduling module is further configured to select at least one CDN device in the CDN device set according to the scheduling policy;
the execution module is used for distributing the request to the selected CDN device for processing;
the scheduling strategy of the current period is calculated in the previous period of the current period;
calculating the scheduling policy of the current cycle comprises:
randomly initializing population genes, wherein each gene corresponds to a scheduling strategy;
predicting the bandwidth of the whole network in the current period, and setting a gene evolution direction according to the bandwidth of the whole network;
evolving initial population genes towards the gene evolution direction based on a genetic algorithm to obtain optimal genes;
determining a scheduling strategy corresponding to the optimal gene as a scheduling strategy of the current period;
wherein, the setting of the gene evolution direction according to the whole network bandwidth comprises:
when the bandwidth of the whole network is larger than the sum of the expected charging bandwidths of the CDN equipment, setting the CDN equipment using free bandwidth at the current moment as a gene evolution direction;
when the bandwidth of the whole network is not less than the sum of the expected cost bandwidths of the CDN equipment and not more than the sum of the expected charging bandwidths of the CDN equipment, setting the cost of the CDN equipment with priority and the service quality as an auxiliary direction of gene evolution;
and when the bandwidth of the whole network is smaller than the sum of the expected cost bandwidths of the CDN equipment, preferentially setting the service quality of the CDN equipment as a gene evolution direction.
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| CN113132437B (en) * | 2019-12-31 | 2024-01-23 | 中兴通讯股份有限公司 | CDN scheduling method, CDN scheduling system, CDN scheduling equipment and storage medium |
| CN111327461B (en) * | 2020-01-23 | 2022-03-11 | 华为云计算技术有限公司 | Domain name management method, device, equipment and medium based on CDN system |
| CN111917898B (en) * | 2020-07-24 | 2021-08-27 | 网宿科技股份有限公司 | Resource scheduling policy adjusting method and device |
| CN112243025B (en) * | 2020-09-22 | 2023-10-17 | 网宿科技股份有限公司 | Node cost scheduling method, electronic equipment and storage medium |
| CN113691463B (en) * | 2021-08-19 | 2022-07-08 | 网宿科技股份有限公司 | CDN scheduling parameter adjusting method and device, electronic equipment and storage medium |
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